Search results for: class C fly ash

Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza

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In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.

Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.

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Authors: A. Thomas, B. John Oommen

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Although the field of parametric Pattern Recognition (PR) has been thoroughly studied for over five decades, the use of the Order Statistics (OS) of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. This must be contrasted with the Bayesian paradigm in which, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding central points, for example, the means. In [2], we showed that the results could be extended for a few symmetric distributions within the exponential family. In this paper, we attempt to extend these results significantly by considering asymmetric distributions within the exponential family, for some of which even the closed form expressions of the cumulative distribution functions are not available. These distributions include the Rayleigh, Gamma and certain Beta distributions. As in [1] and [2], the new scheme, referred to as Classification by Moments of Order Statistics (CMOS), attains an accuracy very close to the optimal Bayes’ bound, as has been shown both theoretically and by rigorous experimental testing.

Keywords: Classification using Order Statistics (OS), Exponential family, Moments of OS

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Authors: M. Nakisa, A. Maimun, Yasser M. Ahmed, F. Behrouzi, A. Tarmizi

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The practical application of the Computational Fluid Dynamics (CFD), for predicting the flow pattern around Multipurpose Amphibious Vehicle (MAV) hull has made much progress over the last decade. Today, several of the CFD tools play an important role in the land and water going vehicle hull form design. CFD has been used for analysis of MAV hull resistance, sea-keeping, maneuvering and investigating its variation when changing the hull form due to varying its parameters, which represents a very important task in the principal and final design stages. Resistance analysis based on CFD (Computational Fluid Dynamics) simulation has become a decisive factor in the development of new, economically efficient and environmentally friendly hull forms. Three-dimensional finite volume method (FVM) based on Reynolds Averaged Navier-Stokes equations (RANS) has been used to simulate incompressible flow around three types of MAV hull bow models in steady-state condition. Finally, the flow structure and streamlines, friction and pressure resistance and velocity contours of each type of hull bow will be compared and discussed.

Keywords: RANS Simulation, Multipurpose Amphibious Vehicle, Viscous Flow Structure.

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Authors: Rozilawati Binti Dollah, Masaki Aono

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Classifying biomedical literature is a difficult and challenging task, especially when a large number of biomedical articles should be organized into a hierarchical structure. In this paper, we present an approach for classifying a collection of biomedical text abstracts downloaded from Medline database with the help of ontology alignment. To accomplish our goal, we construct two types of hierarchies, the OHSUMED disease hierarchy and the Medline abstract disease hierarchies from the OHSUMED dataset and the Medline abstracts, respectively. Then, we enrich the OHSUMED disease hierarchy before adapting it to ontology alignment process for finding probable concepts or categories. Subsequently, we compute the cosine similarity between the vector in probable concepts (in the “enriched" OHSUMED disease hierarchy) and the vector in Medline abstract disease hierarchies. Finally, we assign category to the new Medline abstracts based on the similarity score. The results obtained from the experiments show the performance of our proposed approach for hierarchical classification is slightly better than the performance of the multi-class flat classification.

Keywords: Biomedical literature, hierarchical text classification, ontology alignment, text mining.

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Authors: A. Deswal, N. S. Deora, H. N. Mishra

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The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyze spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), Discriminant Factorial Analysis (DFA) and Soft Independent Modelling by Class Analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable countsshowed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20hrs and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Keywords: Electronic-nose, bacteriological, shelf-life, classification.

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Authors: Hong Son Hoang, Remy Baraille

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This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Keywords: Statistical simulation, canonical form, dynamical system, Markov and non-Markovian processes, data assimilation.

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Authors: Phruksaphanrat B.

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This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

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Authors: L. Parisi

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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: Kinemic gait data, Neural networks, Hip joint implant, Hip arthroplasty, Rehabilitation Engineering.

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Authors: Ghada Moussa, Mamoud Owais

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Transit route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Keywords: Integer programming, Transit route design, Transportation, Urban planning.

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Authors: Ching Kin Keong, Koh Tieng Wei, Abdul Azim Abd. Ghani, Khaironi Yatim Sharif

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Maintaining factory default battery endurance rate over time in supporting huge amount of running applications on energy-restricted mobile devices has created a new challenge for mobile applications developer. While delivering customers’ unlimited expectations, developers are barely aware of efficient use of energy from the application itself. Thus, developers need a set of valid energy consumption indicators in assisting them to develop energy saving applications. In this paper, we present a few software product metrics that can be used as an indicator to measure energy consumption of Android-based mobile applications in the early of design stage. In particular, Trepn Profiler (Power profiling tool for Qualcomm processor) has used to collect the data of mobile application power consumption, and then analyzed for the 23 software metrics in this preliminary study. The results show that McCabe cyclomatic complexity, number of parameters, nested block depth, number of methods, weighted methods per class, number of classes, total lines of code and method lines have direct relationship with power consumption of mobile application.

Keywords: Battery endurance, software metrics, mobile application, power consumption.

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Authors: Yang Song, Yifan Guo, Edward F. Gehringer

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Fifty years of research has found great potential for peer assessment as a pedagogical approach. With peer assessment, not only do students receive more copious assessments; they also learn to become assessors. In recent decades, more educational peer assessments have been facilitated by online systems. Those online systems are designed differently to suit different class settings and student groups, but they basically fall into two categories: rating-based and ranking-based. The rating-based systems ask assessors to rate the artifacts one by one following some review rubrics. The ranking-based systems allow assessors to review a set of artifacts and give a rank for each of them. Though there are different systems and a large number of users of each category, there is no comprehensive comparison on which design leads to higher reliability. In this paper, we designed algorithms to evaluate assessors' reliabilities based on their rating/ranking against the global ranks of the artifacts they have reviewed. These algorithms are suitable for data from both rating-based and ranking-based peer assessment systems. The experiments were done based on more than 15,000 peer assessments from multiple peer assessment systems. We found that the assessors in ranking-based peer assessments are at least 10% more reliable than the assessors in rating-based peer assessments. Further analysis also demonstrated that the assessors in ranking-based assessments tend to assess the more differentiable artifacts correctly, but there is no such pattern for rating-based assessors.

Keywords: Peer assessment, peer rating, peer ranking, reliability.

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Authors: Daniel E. Gberevbie, Adewale O. Osibanjo, Anthonia A. Adeniji, Olumuyiwa A. Oludayo

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Research has shown that a recruitment policy devoid of gender discrimination enhances employee performance in an organization. Previous studies in Nigeria show that gender discrimination against men and women based on their ethnic, religious and geographical identity is common. This survey, however, focuses on discrimination against women on the basis of gender and performance in government universities in Lagos State, Nigeria. The model used for this study was developed and tested in which one hundred and eighty seven copies of the questionnaire that were administered to respondents as completed by the academic staff of government universities in Lagos State were retrieved. Pearson correlation and regression were utilized for the analysis of the study, and the result showed that managerial roles based on gender discrimination against women in government universities in Lagos State have affected employee job performance negatively. The study concludes that for as long as gender discrimination rather than merit remains the basis for staff employment into positions of authority in Nigerian Universities, enhanced performance is more likely to elude employees and the educational sector in general. 

Keywords: Academic staff, Employee performance, Gender discrimination, Nigeria, Universities.

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Authors: Nagasamy Venkatesh Dhandapani, Amged Awad El-Gied

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Cefixime, a BCS class II drug, is insoluble in water but freely soluble in acetone and in alcohol. The aqueous solubility of cefixime in water is poor and exhibits exceptionally slow and intrinsic dissolution rate. In the present study, cefixime and β-Cyclodextrin (β-CD) solid dispersions were prepared with a view to study the effect and influence of β-CD on the solubility and dissolution rate of this poorly aqueous soluble drug. Phase solubility profile revealed that the solubility of cefixime was increased in the presence of β-CD and was classified as A_L-type. Effect of variable, such as drug:carrier ratio, was studied. Physical characterization of the solid dispersion was characterized by Fourier transform infrared spectroscopy (FT-IR) and Differential scanning calorimetry (DSC). These studies revealed that a distinct loss of drug crystallinity in the solid molecular dispersions is ostensibly accounting for enhancement of dissolution rate in distilled water. The drug release from the prepared solid dispersion exhibited a first order kinetics. Solid dispersions of cefixime showed a 6.77 times fold increase in dissolution rate over the pure drug.

Keywords: Cefixime, β-Cyclodextrin, solid dispersions, kneading method, dissolution, release kinetics.

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Authors: Randhir Singh Baghel, Joydip Dhar, Renu Jain

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In this paper, for the understanding of the phytoplankton dynamics in marine ecosystem, a susceptible and an infected class of phytoplankton population is considered in spatiotemporal domain. Here, the susceptible phytoplankton is growing logistically and the growth of infected phytoplankton is due to the instantaneous Holling type-II infection response function. The dynamics are studied in terms of the local and global stabilities for the system and further explore the possibility of Hopf -bifurcation, taking the half saturation period as (i.e., ) the bifurcation parameter in temporal domain. It is also observe that the reaction diffusion system exhibits spatiotemporal chaos and pattern formation in phytoplankton dynamics, which is particularly important role play for the spatially extended phytoplankton system. Also the effect of the diffusion coefficient on the spatial system for both one and two dimensional case is obtained. Furthermore, we explore the higher-order stability analysis of the spatial phytoplankton system for both linear and no-linear system. Finally, few numerical simulations are carried out for pattern formation.

Keywords: Phytoplankton dynamics, Reaction-diffusion system, Local stability, Hopf-bifurcation, Global stability, Chaos, Pattern Formation, Higher-order stability analysis.

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Authors: Elis N. Herliyana , Kunio Tsunoda, Yusuf S. Hadi, Arinana, Dewi A. Natalia

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This study aims to determine the level of resistance of Hevea brasiliensis and Paraserianthes falcataria (synonym: Falcataria molucana) against wood rot fungi Pleurotus ostreatus based on Indonesian standard SNI 01.7207-2006 and Japanese standard JIS K 1571-2004. The variables measured were visual appearance and weight loss percentage of wood based on longitudinal and cross section fiber directions of rubber wood and sengon wood. Measurement of oven dry weight loss of wood samples performed after 12 weeks incubation. Replication performed was 10 times at each treatment combination. The results based on SNI 01.7207-2006, weight loss value of H. brasiliensis and P. falcataria wood with fiber direction longitudinal were 23,12 and 22,25% respectively and cross section were 20,77 and 18,76% respectively, and all were classified to resistance class IV (no resistance). The results based on JIS K 1571-2004, weight loss value of both woods with fiber direction cross section were 10,95 and 14,20% respectively.

Keywords: H. brasiliensis wood, Natural durability, P. falcataria wood, P. ostreatus.

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Authors: Ö.F. Ursavas, H. Karal

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In this study it is aimed to determine the level of preservice teachers- computer phobia. Whether or not computer phobia meaningfully varies statistically according to gender and computer experience has been tested in the study. The study was performed on 430 pre-service teachers at the Education Faculty in Rize/Turkey. Data in the study were collected through the Computer Phobia Scale consisting of the “Personal Knowledge Questionnaire", “Computer Anxiety Rating Scale", and “Computer Thought Survey". In this study, data were analyzed with statistical processes such as t test, and correlation analysis. According to results of statistical analyses, computer phobia of male pre-service teachers does not statistically vary depending on their gender. Although male preservice teachers have higher computer anxiety scores, they have lower computer thought scores. It was also observed that there is a negative and intensive relation between computer experience and computer anxiety. Meanwhile it was found out that pre-service teachers using computer regularly indicated lower computer anxiety. Obtained results were tried to be discussed in terms of the number of computer classes in the Education Faculty curriculum, hours of computer class and the computer availability of student teachers.

Keywords: Computer phobia, computer anxiety, computer thought, pre-service teachers.

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Authors: Fahri Benli, Sitalakshmi Venkatraman, Ye Wei, Fiona Wahr

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A flipped classroom which is a form of blended learning shifts the focus from a teacher-centered approach to a learner-centered approach. However, not all learners are ready to take the active role of knowledge and skill acquisition through a flipped classroom and they continue to delve in a passive mode of learning. This challenges educators in designing, scaffolding and facilitating in-class activities for students to have active learning experiences in a flipped classroom environment. Experiential learning theories have been employed by educators in the past in physical classrooms based on the principle that knowledge could be actively developed through direct experience. However, with more of online teaching witnessed recently, there are inherent limitations in designing and simulating an experiential learning activity for an online environment. In this paper, we explore enhancing experiential learning using smart digital tools that could be employed in a flipped classroom within a higher education setting. We present the use of smart collaborative tools online to enhance the experiential learning activity to teach higher-order cognitive concepts of business process modeling as a case study.

Keywords: Experiential learning, flipped classroom, smart software tools, online learning higher-order learning attributes.

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Authors: I. M. Sujaul, M. A. Sobahan, A. A. Edriyana, F. M. Yahaya, R. M. Yunus

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This study was carried out to investigate the adverse effect of industrial wastewater on surface water quality in Gebeng industrial estate, Pahang, Malaysia. Surface water was collected from six sampling stations. Physicochemical parameters were characterized based on in-situ and ex-situ analysis according to standard methods by American Public Health Association (APHA). Selected heavy metals were determined by using Inductively Coupled Plasma Mass Spectrometry (ICP MS). The results revealed that the concentration of heavy metals such as Pb, Cu, Cd, Cr and Hg were high in samples. The results also showed that the value of Pb and Hg were higher in the wet season in comparison to dry season. According to Malaysia National Water Quality Standard (NWQS) and Water Quality Index (WQI) all the sampling station were categorized as class IV (highly polluted). The present study revealed that the adverse effects of careless disposal of wastes and directly discharge of effluents affected on surface water quality. Therefore, the authorities should implement the laws to ensure the proper practices of wastewater management for environmental sustainability around the study area.

Keywords: Gebeng, heavy metals, waste water, water quality index.

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Authors: Mohammad Jamil Abd AlGhani

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The natural native antioxidants N,N-P-methyl phenyl acetone and N,N-phenyl acetone were isolated from the Iraqi crude oil region of Kirkuk by ion exchange and their structure was characterized by spectral and chemical analysis methods. Tetraline was used as a liquid hydrocarbon to detect the efficiency of isolated molecules at elevated temperature (393 K) that it has physicochemical specifications and structure closed to hydrocarbons fractionated from crude oil. The synthesized universal antioxidant 2,6-ditertiaryisobutyl-p-methyl phenol (Unol) with known stochiometric coefficient of inhibition equal to (2) was used as a model for comparative evaluation at the same conditions. Modified chemiluminescence method was used to find the amount of absorbed oxygen and the induction periods in and without the existence of isolated antioxidants molecules. The results of induction periods and quantity of absorbed oxygen during the oxidation process were measured by manometric installation. It was seen that at specific equal concentrations of N,N-phenyl acetone and N, N-P-methyl phenyl acetone in comparison with Unol at 393 K were with (2) and (2.5) times efficient than do Unol. It means that they had the ability to inhibit the formation of new free radicals and prevent the chain reaction to pass from the propagation to the termination step rather than decomposition of formed hydroperoxides.

Keywords: Antioxidants, chemiluminescence, inhibition, unol.

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Authors: Marco Leite, J. M. Vilas-Boas da Silva, Isabel Duarte de Almeida

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New Product Development (NPD) has got its roots on an Engineering background. Thus, one might wonder about the interest, opportunity, contents and delivery process, if students from soft sciences were involved. This paper addressed «What to teach?» and «How to do it?», as the preliminary research questions that originated the introduced propositions. The curriculum-developer model that was purposefully chosen to adapt the coursebook by pursuing macro/micro strategies was found significant by an exploratory qualitative case study. Moreover, learning was developed and value created by implementing the institutional curriculum through a creative, hands-on, experiencing, problem-solving, problem-based but organized teamwork approach. Product design of an orange squeezer complying with ill-defined requirements, including drafts, sketches, prototypes, CAD simulations and a business plan, plus a website, written reports and presentations were the deliverables that confirmed an innovative contribution towards research and practice of teaching and learning of engineering subjects to non-specialist operations managers candidates.

Keywords: Teaching Engineering to Non-specialists, Operations Managers Education, Teamwork, Product Design and Development, Market- driven NPD, Curriculum development.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Ana Paula P. dos Santos, Claudia R. Andrade, Edson L. Zaparoli

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Pressure loss in ductworks is an important factor to be considered in design of engineering systems such as power-plants, refineries, HVAC systems to reduce energy costs. Ductwork can be composed by straight ducts and different types of fittings (elbows, transitions, converging and diverging tees and wyes). Duct fittings are significant sources of pressure loss in fluid distribution systems. Fitting losses can be even more significant than equipment components such as coils, filters, and dampers. At the present work, a conventional 90^o round elbow under turbulent incompressible airflow is studied. Mass, momentum, and k-e turbulence model equations are solved employing the finite volume method. The SIMPLE algorithm is used for the pressure-velocity coupling. In order to validate the numerical tool, the elbow pressure loss coefficient is determined using the same conditions to compare with ASHRAE database. Furthermore, the effect of Reynolds number variation on the elbow pressure loss coefficient is investigated. These results can be useful to perform better preliminary design of air distribution ductworks in air conditioning systems.

Keywords: Duct fitting, Pressure loss, Elbow.

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Authors: Amir Mirzaei, Rahim Naseri, Parvaneh Vafa, Meysam Moradi

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In order to investigate the effect of drought stress and row spacing on grain yield and associated traits of Mungbean, an experiment was conducted as a factorial in based on randomized complete block design with three replications in Ilam station, Iran during 2008-2009 growing season. This experiment was conducted in four stages on one kind of Mungbean named Gohar. The experimental factors including (80, 110 and 140mm cumulative evaporation from class A pan) and row spacing (25, 50, and 75cm) were selected. The results of the experiment showed that the varieties affected by the treatment showed significant differences. The highest total yield was obtained in the condition in which evaporation of water was 80mm. Of course some traits such as grain yield did not show a significant difference between the conditions in which evaporation of the irrigation water was 80 and 110mm. The traits under study also showed a significant difference to different raw spacing. Row spacing of 50cm had a higher total yield compared to other raw spaces. It was due to the higher number of pods per plant and grain weight. The interaction of drought stress and row spacing showed that in the condition in which the row space is 50 cm and the evaporation of the irrigation water is 80mm, the highest number of grain is achieved.

Keywords: Stress, Grain yield, Mungbean, Row spacing.

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Authors: Rami Rashkovits, Ilana Lavy

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In this study we present our developed formative assessment tool for students' assignments. The tool enables lecturers to define assignments for the course and assign each problem in each assignment a list of criteria and weights by which the students' work is evaluated. During assessment, the lecturers feed the scores for each criterion with justifications. When the scores of the current assignment are completely fed in, the tool automatically generates reports for both students and lecturers. The students receive a report by email including detailed description of their assessed work, their relative score and their progress across the criteria along the course timeline. This information is presented via charts generated automatically by the tool based on the scores fed in. The lecturers receive a report that includes summative (e.g., averages, standard deviations) and detailed (e.g., histogram) data of the current assignment. This information enables the lecturers to follow the class achievements and adjust the learning process accordingly. The tool was examined on two pilot groups of college students that study a course in (1) Object-Oriented Programming (2) Plane Geometry. Results reveal that most of the students were satisfied with the assessment process and the reports produced by the tool. The lecturers who used the tool were also satisfied with the reports and their contribution to the learning process.

Keywords: Computer-based formative assessment tool, science education.

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Authors: Ahmed S. Khan, Amin Karim

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During the past several decades, the economy of each nation has been significantly affected by globalization and technology. Government regulations and private sector standards affect a majority of world trade. Countries have been working together to establish international standards in almost every field. As a result, workers in all sectors need to have an understanding of standards. Engineering and technology students must not only possess an understanding of engineering standards and applicable government codes, but also learn to apply them in designing, developing, testing and servicing products, processes and systems. Accreditation Board for Engineering & Technology (ABET) criteria for engineering and technology education require students to learn and apply standards in their class projects. This paper is a follow-up of a 2006-2009 NSF initiative awarded to IEEE to help develop tutorials and case study modules for students and encourage standards education at college campuses. It presents the findings of a faculty/institution survey conducted through various U.S.-based listservs representing the major engineering and technology disciplines. The intent of the survey was to the gauge the status of use of standards and regulations in engineering and technology coursework and to identify benchmark practices. In light of survey findings, recommendations are made to standards development organizations, industry, and academia to help enhance the use of standards in engineering and technology curricula.

Keywords: Standards, regulations, ABET, IEEE, engineering and technology curricula.

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Authors: Ritu Vijay, Rekha Govil

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The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Dyah E. Herwindiati

Abstract:

A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paper

Keywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance

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Authors: Arundhati Devi Maibam, K. Ingocha Singh

Abstract:

Cervical cancer is preventable if detected early. Determination of risk factors is essential to plan screening programmes to prevent the disease. To study the demographic risk factors of cervical cancer among Manipuri women, information on age, marital status, educational level, monthly family income and socioeconomic status were collected through a pre-tested interview schedule. In this study, 64 incident cases registered at the RT Dept, RIMS (Regional Institute of Medical Sciences), Imphal, Manipur, India during 2008-09 participated. Data were entered in Microsoft Excel and the results were expressed in percentages. Among the 64 patients with cervical cancer, 56 (88.9%) were in the age group of 40+ years. The majority of the patients were from rural areas (68.75%) and 31.25% were from urban areas. The majority of the patients were Hindus (73%), 55(85.9%) were of low educational level, 43(67.2%) were married, and 36 (56.25%) belonged to Class IV socioeconomic status. In conclusion, if detected early, cervical cancer is preventable and curable. The potential risk factors need to be identified and women in the risk group need to be motivated for screening. Affordable screening programmes and health care resources will help in lessening the burden of the disease.

Keywords: Cervical cancer, Manipuri women, RIIMS, Socio-demographic risk factors.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

Abstract:

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: Ehab Mourtaga, Ahmad Sharieh, Mousa Abdallah

Abstract:

An automatic speech recognition system for the formal Arabic language is needed. The Quran is the most formal spoken book in Arabic, it is spoken all over the world. In this research, an automatic speech recognizer for Quranic based speakerindependent was developed and tested. The system was developed based on the tri-phone Hidden Markov Model and Maximum Likelihood Linear Regression (MLLR). The MLLR computes a set of transformations which reduces the mismatch between an initial model set and the adaptation data. It uses the regression class tree, as well as, estimates a set of linear transformations for the mean and variance parameters of a Gaussian mixture HMM system. The 30th Chapter of the Quran, with five of the most famous readers of the Quran, was used for the training and testing of the data. The chapter includes about 2000 distinct words. The advantages of using the Quranic verses as the database in this developed recognizer are the uniqueness of the words and the high level of orderliness between verses. The level of accuracy from the tested data ranged 68 to 85%.

Keywords: Hidden Markov Model (HMM), MaximumLikelihood Linear Regression (MLLR), Quran, Regression ClassTree, Speech Recognition, Speaker-independent.

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